Multi-valued Representation of Neutrosophic Information

@inproceedings{Patrascu2014MultivaluedRO,
  title={Multi-valued Representation of Neutrosophic Information},
  author={Vasile Patrascu},
  booktitle={IPMU},
  year={2014}
}
  • V. Patrascu
  • Published in IPMU 15 July 2014
  • Computer Science
The paper presents three variants for multi-valued representation of neutrosophic information. These three representations are provided in the framework of multi-valued logics and it provides some calculation formulae for the following neutrosophic features: truth, falsity, neutrality, undefinedness, saturation, contradiction, ambiguity. In addition, it was defined net-truth, definedness, neutrosophic score and neutrosophic indeterminacy. 
The Neutrosophic Entropy and its Five Components
This paper presents two variants of penta-valued representation for neutrosophic entropy. The first is an extension of Kaufmann's formula and the second is an extension of Kosko's formula. Based on
Entropy, neutro-entropy and anti-entropy for neutrosophic information
TLDR
This approach presents a multi-valued representation of the neutrosophic information that highlights the link between the bifuzzy information and neutrosophile one and construction of two new concepts for the neutro-entropy and anti-ent entropy.
Penta and Hexa Valued Representation of Neutrosophic Information
TLDR
A nuanced representation in a penta valued fuzzy space, described by the index of truth,index of falsity, index of ignorance,Index of contradiction and index of hesitation is defined.
Penta and Hexa Valued Representation of Neutrosophic Information
TLDR
A nuanced representation in a penta valued fuzzy space, described by the index of truth,index of falsity, index of ignorance,Index of contradiction and index of hesitation is defined.
Refined Neutrosophic Information Based on Truth, Falsity, Ignorance, Contradiction and Hesitation
TLDR
This representation can be useful when the neutrosophic information is obtained from bipolar infor- mation which is defined by the degree of truth and thedegree of falsity to which is added the third parameter, its cumulative degree of imprecision.
Neutrosophic Sets and Systems
Singh et al. [1], for solving the fully neutrosophic linear programming problems stated that the method of Abdel-Basset et al. [2] is scientifically incorrect and suggested a modified version for it.

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